This repository contains code for metric learning-based recognition using PyTorch. Metric learning is a technique for learning similarity or distance metrics between data points. In the context of recognition, it helps improve the classification accuracy, especially in cases with imbalanced datasets and few-shot learning scenarios.

• Extract embeddings from images using pre-trained models.
• Train the recognition model.
• Add new classes to the existing model and update embeddings.

Before running the code, make sure you have the following dependencies installed:

• PyTorch
• PyTorch Metric Learning
• torchvision
• Pillow (PIL)

You can install the required packages using the following command:

pip install -r requirements.txt

Feel free to contribute to this project by opening issues or pull requests. Your feedback and contributions are welcome.